Senior AI/ML Engineer

Senior AI/ML Engineer

Senior AI/ML Engineer
Job Details:
Compensation: $160,000 - $200,000
Work Environment: Hybrid (2 days onsite)
Office Location: Glenview, IL
Benefits: Health, Dental, Vision, 401K, PTO, Strong employer contribution to retirement

Key Responsibilities

• Design, develop, deploy, and support AI-powered applications, copilots, agents, and workflow automations.
• Build production-ready AI solutions using LLMs, RAG, vector databases, embeddings, semantic search, and prompt engineering.
• Develop AI agents that securely leverage enterprise data, knowledge repositories, APIs, and business workflows.
• Integrate AI solutions with cloud platforms, enterprise systems, and collaboration tools across Azure and AWS.
• Create reusable AI components, prompts, connectors, and frameworks to accelerate future AI development.
• Partner with business and technical stakeholders to translate use cases into scalable AI products with measurable business impact.
• Ensure AI solutions meet enterprise standards for security, governance, privacy, and responsible AI.

Required Qualifications

• 7+ years of software engineering experience, including 2+ years building enterprise AI solutions.
• Hands-on experience with:
• LLM application development
• RAG architectures
• Prompt engineering
• Embeddings and vector search
• LLM APIs and model evaluation
• Agentic AI and workflow orchestration
• Strong Python development skills and hands-on experience with AI/ML technologies.
• Experience building LLM-based applications using RAG, prompt engineering, embeddings, vector search, and agentic AI frameworks.
• Proven success delivering production-ready AI solutions that drive automation, productivity, or business efficiency.
• Experience deploying and supporting applications in Azure and/or AWS environments.

Preferred Qualifications

• Experience with Azure AI Foundry, Azure AI Search, Copilot Studio, Amazon Bedrock, SageMaker, Pinecone, OpenSearch, or similar AI platforms.
• Knowledge of NLP, semantic search, vector databases, and model evaluation.
• Experience integrating AI solutions through APIs, containers, Azure Functions, or AWS Lambda.
• Familiarity with AI governance, security, and responsible AI best practices.

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